{"id":"W4416799049","doi":"10.1109/icriset64803.2025.11252179","title":"Surface Roughness Classification Using Attention-Guided Convolutional Neural Networks on Real-Time Machining Sensor Data","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Machining; Convolutional neural network; Surface roughness; Python (programming language); Pattern recognition (psychology); Artificial neural network; Surface finish","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002886219,0.0009239308,0.0003974818,0.0007156006,0.0001660546,0.0004093904,0.0006986897,0.0004802059,0.0007659025],"category_scores_gemma":[0.001129997,0.000184958,0.0004516244,0.0004543876,0.0002301775,0.0005012294,0.0004642048,0.0005585087,0.0003150816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000653486,"about_ca_system_score_gemma":0.0004064723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01563108,"about_ca_topic_score_gemma":0.02268519,"domain_scores_codex":[0.999774,0.0000188383,0.000008523701,0.00008677293,0.00005834032,0.00005337449],"domain_scores_gemma":[0.9996942,0.00009289983,0.00005164982,0.0000484996,0.00009423949,0.00001848433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006741306,0.0003593567,0.01759505,0.0001427747,0.0001707889,0.0002953905,0.00009544952,0.4427913,0.07694933,0.0008305814,0.006725503,0.4533703],"study_design_scores_gemma":[0.000004674688,0.00002797891,0.003894483,0.000003946379,0.00001115196,0.0000173762,0.000008397876,0.9890859,0.006414645,0.0002806495,0.0002447691,0.000005971581],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7559673,0.0009988035,0.2319378,0.0003636424,0.0001461921,0.00006727854,0.001254464,0.005898049,0.003366499],"genre_scores_gemma":[0.9723674,0.0001329847,0.02431591,0.00008075719,0.00002560145,0.00002407921,0.001424727,0.00005567468,0.001572799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01563108,"threshold_uncertainty_score":0.03108019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05644453446440733,"score_gpt":0.3232804374903993,"score_spread":0.266835903025992,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}